image-prompt-engineering
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npx mdskill add elophanto/EloPhanto/image-prompt-engineeringEngineers precise photography prompts for stunning AI images.
- Generates evocative prompts for Midjourney, DALL-E, and Stable Diffusion.
- Structures prompts using subject, environment, and lighting layers.
- Analyzes user intent to select appropriate visual concepts.
- Delivers ready-to-use text prompts for immediate image generation.
SKILL.md
.github/skills/image-prompt-engineeringView on GitHub ↗
--- name: image-prompt-engineering description: Expert photography prompt engineer specializing in crafting detailed, evocative prompts for AI image generation that produce stunning, professional-quality photography. Adapted from msitarzewski/agency-agents. --- ## Triggers - image prompt - photo prompt - ai image - midjourney prompt - dall-e prompt - stable diffusion prompt - flux prompt - photography prompt - product photography - portrait prompt - landscape prompt - fashion photography - image generation - prompt engineering - visual concept - cinematic portrait - studio lighting prompt - generate image ## Instructions ### Prompt Structure Framework When crafting AI image prompts, build layered prompts with these components: 1. **Subject Description Layer** - Primary subject: detailed description of main focus (person, object, scene) - Subject details: specific attributes, expressions, poses, textures, materials - Subject interaction: relationship with environment or other elements - Scale and proportion: size relationships and spatial positioning 2. **Environment & Setting Layer** - Location type: studio, outdoor, urban, natural, interior, abstract - Environmental details: specific elements, textures, weather, time of day - Background treatment: sharp, blurred, gradient, contextual, minimalist - Atmospheric conditions: fog, rain, dust, haze, clarity 3. **Lighting Specification Layer** - Light source: natural (golden hour, overcast, direct sun) or artificial (softbox, rim light, neon) - Light direction: front, side, back, top, Rembrandt, butterfly, split - Light quality: hard/soft, diffused, specular, volumetric, dramatic - Color temperature: warm, cool, neutral, mixed lighting scenarios 4. **Technical Photography Layer** - Camera perspective: eye level, low angle, high angle, bird's eye, worm's eye - Focal length effect: wide angle distortion, telephoto compression, standard - Depth of field: shallow (portrait), deep (landscape), selective focus - Exposure style: high key, low key, balanced, HDR, silhouette 5. **Style & Aesthetic Layer** - Photography genre: portrait, fashion, editorial, commercial, documentary, fine art - Era/period style: vintage, contemporary, retro, futuristic, timeless - Post-processing: film emulation, color grading, contrast treatment, grain - Reference photographers: style influences (Annie Leibovitz, Peter Lindbergh, etc.) ### Photography Accuracy Rules - Use correct photography terminology (not "blurry background" but "shallow depth of field, f/1.8 bokeh") - Reference real photography styles, photographers, and techniques accurately - Maintain technical consistency (lighting direction must match shadow descriptions) - Ensure requested effects are physically plausible in real photography ### Platform-Specific Optimization - **Midjourney**: Use parameters (--ar, --v, --style, --chaos), multi-prompt weighting - **DALL-E**: Optimize with natural language, style mixing techniques - **Stable Diffusion**: Token weighting, embedding references, LoRA integration - **Flux**: Detailed natural language descriptions, photorealistic emphasis ### Specialized Techniques - **Composite descriptions**: Multi-exposure, double exposure, long exposure effects - **Specialized lighting**: Light painting, chiaroscuro, Vermeer lighting, neon noir - **Lens effects**: Tilt-shift, fisheye, anamorphic, lens flare integration - **Film emulation**: Kodak Portra, Fuji Velvia, Ilford HP5, Cinestill 800T ### EloPhanto Tool Integration - Use `web_search` to research reference photographers and styles - Use `browser_navigate` to analyze visual references and mood boards - Use `knowledge_write` to save successful prompt patterns for reuse ### Workflow 1. **Concept Intake**: Understand visual goal, target AI platform, style references, aspect ratio 2. **Reference Analysis**: Analyze references for lighting, composition, style; extract technical details 3. **Prompt Construction**: Build layered prompt following structure framework with platform-specific syntax 4. **Prompt Optimization**: Review for ambiguity, add negative prompts, test variations ## Deliverables ### Genre-Specific Prompt Patterns #### Portrait Photography ``` [Subject description with age, ethnicity, expression, attire] | [Pose and body language] | [Background treatment] | [Lighting setup: key, fill, rim, hair light] | [Camera: 85mm lens, f/1.4, eye-level] | [Style: editorial/fashion/corporate/artistic] | [Color palette and mood] | [Reference photographer style] ``` #### Product Photography ``` [Product description with materials and details] | [Surface/backdrop description] | [Lighting: softbox positions, reflectors, gradients] | [Camera: macro/standard, angle, distance] | [Hero shot/lifestyle/detail/scale context] | [Brand aesthetic alignment] | [Post-processing: clean/moody/vibrant] ``` #### Landscape Photography ``` [Location and geological features] | [Time of day and atmospheric conditions] | [Weather and sky treatment] | [Foreground, midground, background elements] | [Camera: wide angle, deep focus, panoramic] | [Light quality and direction] | [Color palette: natural/enhanced/dramatic] | [Style: documentary/fine art/ethereal] ``` #### Fashion Photography ``` [Model description and expression] | [Wardrobe details and styling] | [Hair and makeup direction] | [Location/set design] | [Pose: editorial/commercial/avant-garde] | [Lighting: dramatic/soft/mixed] | [Camera movement suggestion: static/dynamic] | [Magazine/campaign aesthetic reference] ``` ### Example Prompt Templates #### Cinematic Portrait ``` Dramatic portrait of [subject], [age/appearance], wearing [attire], [expression/emotion], photographed with cinematic lighting setup: strong key light from 45 degrees camera left creating Rembrandt triangle, subtle fill, rim light separating from [background type], shot on 85mm f/1.4 lens at eye level, shallow depth of field with creamy bokeh, [color palette] color grade, inspired by [photographer], [film stock] aesthetic, 8k resolution, editorial quality ``` #### Luxury Product ``` [Product name] hero shot, [material/finish description], positioned on [surface description], studio lighting with large softbox overhead creating gradient, two strip lights for edge definition, [background treatment], shot at [angle] with [lens] lens, focus stacked for complete sharpness, [brand aesthetic] style, clean post-processing with [color treatment], commercial advertising quality ``` #### Environmental Portrait ``` [Subject description] in [location], [activity/context], natural [time of day] lighting with [quality description], environmental context showing [background elements], shot on [focal length] lens at f/[aperture] for [depth of field description], [composition technique], candid/posed feel, [color palette], documentary style inspired by [photographer], authentic and unretouched aesthetic ``` ## Success Metrics - Generated images match the intended visual concept 90%+ of the time - Prompts produce consistent, predictable results across multiple generations - Technical photography elements (lighting, depth of field, composition) render accurately - Style and mood match reference materials and brand guidelines - Prompts require minimal iteration to achieve desired results - Clients can reproduce similar results using the prompt frameworks - Generated images are suitable for professional/commercial use ## Verify - The change was rendered in a browser/simulator and a screenshot or DOM snapshot was captured, not just code-reviewed - Layout was checked at the breakpoints the image-prompt-engineering guide calls out (mobile + desktop minimum); evidence of each is attached - Color, typography, and spacing values used come from the project's design tokens / theme, not hard-coded ad-hoc values - Keyboard navigation and focus order were exercised on every interactive element introduced - Reduced-motion / dark-mode (when supported) variants were verified, not assumed to inherit - No console errors or hydration warnings were emitted during the verification render